Lead application Adaptive edge AI systems for industrial application
Based on our research, it will be possible to integrate artificial intelligence directly into the sensor and thus derive decisions in real time without detouring via the cloud. The automated adaptation to new environmental conditions can open up versatile fields of application.
These solutions can be used to detect fault conditions or wear directly in the process or to implement measurement systems for maintenance that enable direct evaluation based on the sensor data. This makes an active contribution to the conservation of resources (computing time, communication overhead).
Contact
Contact
Dr.-Ing. Tino Hutschenreuther
Head of System Design
tino.hutschenreuther(at)imms.de+49 (0) 3677 874 93 40
Dr. Tino Hutschenreuther will answer your questions on our research in Smart distributed measurement and test systems and the related core topics Analysis of distributed IoT systems, Embedded AI and Real-time data processing and communications, on the lead applications Adaptive edge AI systems for industrial application and IoT systems for cooperative environmental monitoring as well as on the range of services for the development of embedded systems.
Related content

Project
Trib.US
IMMS develops real-time capable platform and algorithms for mobile multi-sensor inspection device for conveyor belt maintenance

Project
thurAI
In thurAI, IMMS is working on sensor technology for SmartCity and methods to intelligently process data in the network for AI evaluations.

Project
KIQ
IMMS has developed an AI-based, retrofittable and cost-effective solution for quality assurance of machining tools.

Project
sUSe
To use compressed air for industrial processes in an energy-efficient way, IMMS has developed the electronics platform for an automatable sensor solution.
Reference
Prof. Dr. Peter Holstein, SONOTEC GmbH
“IMMS has designed the digital components of the hardware to be used in our new digital ultrasonic testing device. The signal processing performance achieved is largely based on FPGA technology, a field in which IMMS has excellent references. Our joint work with IMMS went off perfectly.”
Trade-off between Spectral Feature Extractors for Machine Health Prognostics on Microcontrollers
Umut Onus1. Sebastian Uziel1. Tino Hutschenreuther1. Silvia Krug1,2.The IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA 2022), 15 - 17 June 2022, Chemnitz, Germany
1IMMS Institut für Mikroelektronik- und Mechatronik-Systeme gemeinnützige GmbH, 98693 Ilmenau, Germany. 2Mid Sweden University, Sundsvall, Sweden.Learn from error! ML-based model error estimation for design verification without false-positives
Henning Siemen1. Martin Grabmann1. Georg Gläser1.2022 19th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD), 12 - 15 June 2022, Villasimius, Sardinia, Italy
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1IMMS Institut für Mikroelektronik- und Mechatronik-Systeme gemeinnützige GmbH, Ehrenbergstraße 27, 98693 Ilmenau, Germany. 2TU Ilmenau, 98693 Ilmenau, Germany.Überwachung von Druckluftanlagen zum Einsparen von Ressourcen
Sebastian Uziel1.Veranstaltungsreihe Ressourceneffizienz vor Ort – Digitalisierung & Ressourceneffizienz, 26. November 2019, Industrie- und Handelskammer Südthüringen, Suhl
1IMMS Institut für Mikroelektronik- und Mechatronik-Systeme gemeinnützige GmbH, 98693 Ilmenau, Germany.